revix_classifier / README.md
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metadata
library_name: transformers
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: revix_classifier
    results: []

revix_classifier

This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4733
  • Accuracy: 0.9292
  • Precision: 0.9492
  • Recall: 0.9106
  • F1: 0.9295

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.4055 1.0 120 0.4456 0.8 0.7698 0.8699 0.8168
0.4578 2.0 240 0.4217 0.875 0.8345 0.9431 0.8855
0.2235 3.0 360 0.4959 0.85 0.9780 0.7236 0.8318
0.092 4.0 480 0.3820 0.9083 0.9391 0.8780 0.9076
0.2152 5.0 600 0.5537 0.8792 0.8615 0.9106 0.8854
0.0612 6.0 720 0.4747 0.9292 0.9417 0.9187 0.9300
0.0382 7.0 840 0.4424 0.925 0.9412 0.9106 0.9256
0.0015 8.0 960 0.4647 0.925 0.9646 0.8862 0.9237
0.0005 9.0 1080 0.4684 0.9292 0.9492 0.9106 0.9295
0.0006 10.0 1200 0.4733 0.9292 0.9492 0.9106 0.9295

Framework versions

  • Transformers 4.56.1
  • Pytorch 2.8.0+cu126
  • Datasets 4.0.0
  • Tokenizers 0.22.0